2018-03-22 22:11

3 files changed, 48 insertions, 1 deletions

diff --git a/dissertation.cls b/dissertation.cls
index 4e8adc8..3769526 100644
--- a/dissertation.cls
+++ b/dissertation.cls
@@ -86,7 +86,7 @@
 \usemintedstyle{colorfuli}
 \setminted[python]{linenos=false, frame=none}
 
-\definecolor{bg}{rgb}{0.95,0.95,0.95}
+\definecolor{bg}{rgb}{0.95, 0.95, 0.95}
 
 \setmintedinline[python]{bgcolor=bg}
 
@@ -100,6 +100,8 @@
   arc=0,
   shadow=false,
   boxsep=1ex, top=0pt, left=0pt, right=0pt, bottom=0pt,
+  title={\hfill(\arabic{chapter}.\arabic{equation})},
+  list entry={\hfill(\arabic{chapter}.\arabic{equation})},
   comment={\hfill(\arabic{chapter}.\arabic{equation})},
   listing outside comment,
   righthand width=2.5em,
diff --git a/dissertation.pdf b/dissertation.pdf
index 2371c9c..6db6bd2 100644
--- a/dissertation.pdf
+++ b/dissertation.pdf
diff --git a/processing/chapter.tex b/processing/chapter.tex
index 3225624..72d1d27 100644
--- a/processing/chapter.tex
+++ b/processing/chapter.tex
@@ -281,6 +281,51 @@ Also consider using the fit sub-package.  % TODO: more info, link to section
 

 Chop is one of the most important methods of data, although it is typically not called directly by

 users of WrightTools.  %

+Chop takes n-dimensional data and ``chops'' it into all of it's lower dimensional components.  %

+Consider a 3D dataset in \python{('wm', 'w2', 'w1')}.  %

+This dataset can be chopped to it's component 2D \python{('wm', 'w1')} spectra.  %

+\begin{codefragment}{python, label=test_label}

+>>> import WrightTools as wt; from WrightTools import datasets

+>>> data = wt.data.from_PyCMDS(datasets.PyCMDS.wm_w2_w1_000)

+data created at /tmp/lzyjg4au.wt5::/

+  axes ('wm', 'w2', 'w1')

+  shape (35, 11, 11)

+>>> chopped = data.chop('wm', 'w1')  

+chopped data into 11 piece(s) in ('wm', 'w1')

+>>> chopped.chop000

+<WrightTools.Data 'chop000' ('wm', 'w1') at /tmp/935c2v5a.wt5::/chop000>

+\end{codefragment}

+\python{chopped} is a collection containing 11 data objects: \python{chop000, chop001 ...

+  chop010}.  %

+Note that, by default, the collection is made at the root level of a new tempfile.  %

+An optional keyword argument \python{parent} allows users to specify the destination for this new

+collection.   %

+These lower dimensional data objects can then be used in plotting routines, fitting routines etc.  %

+

+By default, chop returns \emph{all} of the lower dimensional slices.  %

+Considering the same data object from \autoref{test_label}, we can choose to get all 1D wm

+slices.  %

+\begin{codefragment}{python}

+>>> chopped = data.chop('wm')

+chopped data into 121 piece(s) in ('wm',)

+>>> chopped.chop000

+<WrightTools.Data 'chop000' ('wm',) at /tmp/pqkbc0qr.wt5::/chop000>

+\end{codefragment}

+

+If desired, users may use the \python{at} keyword argument to specify a particular coordinate in

+the un-retained dimensions.  %

+For example, suppose that you want to plot the data from \ref{test_label} as an wm, w1 plot at

+w2 = 1580 wn.  %

+\begin{codefragment}{python}

+>>> chopped = data.chop('wm', 'w1', at={'w2': [1580, 'wn']})[0]

+chopped data into 1 piece(s) in ('wm', 'w1')

+>>> chopped

+<WrightTools.Data 'chop000' ('wm', 'w1') at /tmp/_yhrdprp.wt5::/chop000>

+>>> chopped.w2.points

+array([1580.0])

+\end{codefragment}

+Note the [0]...  % TODO

+This same syntax used in artists...  % TODO

 

 \subsubsection{Collapse}